Course # 30545 Section Number 2 Day(s) M- W Time(s) 1:30pm-2:50pm Term Fall 2025 Specialization Data Analytics Course Instructor Chris Clapp Syllabus Syllabus 1/6/25 The objective of this course is to train students to be insightful users of modern machine-learning methods. The class covers regularization methods for regression and classification, as well as large-scale approaches to inference and testing. In order to have greater flexibility when analyzing datasets, both frequentist and Bayesian methods are investigated. This class is required for the Data Analytic specialization but is open to all students who have taken the Harris core statistics classes (or the equivalent) and have some exposure to programming. Notes Students must register separately for both a lecture (PPHA 30545) and a discussion (PPHA 30547). Attendance at discussions is optional but encouraged for this course. Recent News More news University of Chicago’s Harris School of Public Policy and Institute for Climate and Sustainable Growth Launch New Pathbreaking Master’s Program in Climate and Energy Policy Tue., July 08, 2025 Provost Katherine Baicker Appointed Emmett Dedmon Distinguished Service Professor Thu., July 03, 2025 Alumni Profile: Daisuke Kageyama, MPP'23 Thu., June 26, 2025 Upcoming Events More events Get to Know Harris! A Virtual Information Session Wed., July 09, 2025 | 8:30 AM Harris Alumni Roundtables in Washington, DC: Transitions between public and private sector roles Wed., July 09, 2025 | 8:30 AM Office of Federal Relations 1730 Pennsylvania Ave NW Washington, DC 20006 United States Harris Summer Mixer in Washington, DC: Cultivating Policy Connections Thu., July 10, 2025 | 5:00 PM Harris Summer Mixer in Washington, DC: Cultivating Policy Connections Office of Federal Relations 1730 Pennsylvania Ave NW Washington,, DC 20006 United States